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30:52

Jeremy Pollack of Ancestry.com on Test-driven Development and More

Posted by Jeremy Pollack on  Feb 15, 2014

Hadoop, the distributive file system and MapReduce are just a few of the topics covered in this interview recorded live at QCon San Francisco 2013. Industry-standard Agile implementation and a lot of testing, assures the development team at Ancestry.com that they have an app that can handle the large traffic demands of the popular genealogy site.

27:41

Eva Andreasson on Hadoop, the Hadoop Ecosystem, Impala

Posted by Eva Andreasson on  Nov 11, 2013 1

Eva Andreasson explains the various Hadoop technologies and how they interact, real-time queries with Impala, the Hadoop ecosystem including Hue, Oozie, YARN, and much more.

Ken Little on Scaling Tumblr

Posted by Ken Little on  Sep 24, 2012

Ken Little talks about scaling Tumblr to keep up with their blogging users: scaling the data model, sharding, their PHP frontend and the Scala backend, and much more.

Big Data Architecture at LinkedIn

Posted by Siddharth Anand on  May 14, 2012 1

In this interview at QCon London, LinkedIn’s Sid Anand discusses the problems they face when serving high-traffic, high-volume data. Sid explains how they’re moving some use cases from Oracle to gain headroom, and lifts the hood on their open source search and data replication projects, including Kafka, Voldemort, Espresso and Databus.

Attila Szegedi on JVM and GC Performance Tuning at Twitter

Posted by Attila Szegedi on  Feb 09, 2012 3

Attila Szegedi talks about performance tuning Java and Scala programs at Twitter: how to approach GC problems, the importance of asynchronous I/O, when to use MySQL/Cassandra/Redis, and much more.

What’s Next for jclouds?

Posted by Adrian Cole on  Dec 23, 2010

Adrian Cole discusses his jclouds project, which is an open source library that helps Java developers get started in the cloud and reuse their Java development skills. Cole also talks about some of the challenges of creating a cloud agnostic library, such as the use of different hypervisors and that various cloud implementations are written in different languages, such as VB, Python, Ruby, etc.

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